Programa do Curso
Day 1
Foundations of Data Products & Strategy
Introduction to Modern Data Products
Data Products versus Traditional Data Systems
Data as a Strategic Business Asset
Key Components of a Data Product Ecosystem
Identifying Business Problems Suitable for Data Products
Overview of the Data Product Lifecycle (from Ideation to Scaling)
Case Studies: Successful Data Products in Industry
Day 2
Data Product Design & Architecture
Principles of Data Product Design
Understanding User Personas and Data Consumers
Data Architecture Models (Centralized versus Data Mesh versus Hybrid)
Designing Scalable Data Pipelines
Data Modeling for Analytics and Operational Use
APIs and Data Accessibility Layers
Cloud Infrastructure for Data Products (Overview of AWS, Azure, GCP)
Day 3
Data Engineering & Implementation
Data Ingestion Methods (Batch versus Streaming)
ETL versus ELT Frameworks
Building Reliable Data Pipelines
Data Storage Solutions (Data Lakes, Warehouses, Lakehouse)
Data Transformation and Orchestration Tools
Introduction to Real-Time Data Processing
Hands-on Lab: Building a Simple Data Pipeline
Day 4
Analytics, AI Integration & Governance
Integrating Analytics into Data Products
Dashboards, KPIs, and Decision Intelligence
Introduction to AI/ML in Data Products
Recommendation Systems and Predictive Models
Data Quality Management and Monitoring
Data Governance, Privacy, and Compliance (Overview of GDPR concepts)
Ensuring Trust, Security & Reliability in Data Products
Day 5
Deployment, Scaling & Productization
Productizing Data Solutions for End Users
Deployment Strategies and CI/CD for Data Products
Monitoring, Performance Optimization & Scaling
Data Product Lifecycle Management in Organizations
Monetization Strategies for Data Products
Future Trends: Generative AI & Autonomous Data Products
Capstone Project Presentation & Feedback Session
Requisitos
- Recomenda-se um conhecimento básico de conceitos de dados e relatórios empresariais.
- A familiaridade com o Excel ou qualquer ferramenta básica de análise de dados é útil.
- A consciência de como os dados apoiam a tomada de decisões empresariais será benéfica.
- Não é necessário background avançado em programação ou técnico.
- É essencial o interesse por dados, análises e desenvolvimento de produtos digitais.
Testemunhos de Clientes (2)
A variedade das informações compartilhadas e a clareza ao explicar termos em linguagem simples.
Arisbe Mendoza - Fairtrade International
Curso - GDPR Workshop
Máquina Traduzida
É uma sessão prática.
Vorraluck Sarechuer - Total Access Communication Public Company Limited (dtac)
Curso - Talend Open Studio for ESB
Máquina Traduzida
